The present invention relates generally to the field of data processing, and more particularly to faceted classification of search results.
Document retrieval systems accept a search query and generate a result, which is a set of documents. Queries are often specified by imposing conditions on document metadata (e.g. title, author, year, etc.). Sometimes the documents are representative of real objects, for example, an online catalog lets customers search for products to buy. Result sets are often sorted according to some criteria (e.g. ascending cost). Additional useful information which can be presented in response to a query is a classification of the results according to metadata that is not included in the original query, i.e., showing how the set of results is composed, according to specific “classes” of a property. For example, when searching an online catalog for a television, a certain number of results are identified, and the set of results is subdivided according to one category (e.g. dimension in inches) and subtotals are shown for each one of the possible values of the class (3 results for “17 inches”, 5 for “20 inches”, 12 for “22 inches”, 2 for “25 inches”, etc.). This kind of result classification is called faceting.
Faceting is often applied on many different categories at the same time, projecting the result set along orthogonal directions. For example, televisions can be classified according to size, manufacturer, technology, cost range, weight, etc. Faceted searches are maximally useful when a user is trying to identify the best choice among a number of proposals. The usual operation involves a wide query, giving a big result set which is faceted among many axes, each axis subdivided into different subcategories. The user reduces the result set by selecting one or more of the facet values. The additional condition is added to the query, and facets are recalculated.